Skip to main content

Realtime quality control for mass spectrometry data acquisition

Project description

MS-AutoQC

MS-AutoQC is an all-in-one solution for automated quality control of liquid chromatography-mass spectrometry (LC-MS) data, both during and after data acquisition.


It offers a fast, straightforward approach to ensure collection of high-quality data, allowing for less time investigating raw data and more time conducting experiments.

Developed at the Mass Spectrometry Platform of CZ Biohub San Francisco, MS-AutoQC provides a host of key features to streamline untargeted metabolomics research, such as:

  • Automated and user-defined quality control checks during instrument runs
  • Realtime updates on QC fails in the form of Slack or email notifications
  • Interactive data visualization of internal standard retention time, m/z, and intensity across samples
  • Google Drive cloud sync and secure, Google-authenticated access to QC results from any device

Requirements

MS-AutoQC was designed to run on Windows platforms because of its dependency on MSConvert for vendor format data conversion and MS-DIAL for data processing and identification. However, MacOS users can still use MS-AutoQC to monitor / view their instrument run data.

In addition, MS-AutoQC requires Python 3.8+ and various Python packages, including Pandas, SQLAlchemy, Plotly, Dash, Bootstrap, Watchdog, Google API, and Slack API. These are installed automatically during setup.

Note: Installation of Python and various Python packages on MS instrument computers comes at no risk. For extra security and peace of mind, you can opt to install MS-AutoQC in a virtual environment. To learn more, please read the installation guide.

Installation

Installing MS-AutoQC is easy. Simply open your Terminal or Command Prompt and type:

pip install ms-autoqc

Python dependencies are installed automatically, but dependencies such as MSConvert and MS-DIAL will need to be installed manually. Check out the installation guide for more details.

If necessary, you can download and install MS-AutoQC v1.0.0 manually from GitHub – although we strongly recommend using pip!

Please keep in mind that MS-AutoQC is still in beta development. If you encounter a bug or issue, please report it by opening an issue on GitHub.

Supported Vendors

MS-AutoQC was designed to be a universal, open-source solution for data quality control. Because MSConvert converts raw acquired data into open mzML format before routing it to the data processing pipeline, the package will work seamlessly with data of all vendor formats.

However, MS-AutoQC has only been tested extensively on Thermo Fisher mass spectrometers and Thermo RAW files. As such, it is expected that there may be bugs / issues with processing data of other vendor formats.

We are welcome to collaboration! If you would like to help us comprehensively test support on Agilent / Bruker / Sciex / Waters instruments, please send an email to brian.defelice@czbiohub.org.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

ms-autoqc-1.0.1.tar.gz (115.5 kB view details)

Uploaded Source

Built Distribution

ms_autoqc-1.0.1-py3-none-any.whl (115.2 kB view details)

Uploaded Python 3

File details

Details for the file ms-autoqc-1.0.1.tar.gz.

File metadata

  • Download URL: ms-autoqc-1.0.1.tar.gz
  • Upload date:
  • Size: 115.5 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.11.2

File hashes

Hashes for ms-autoqc-1.0.1.tar.gz
Algorithm Hash digest
SHA256 b845e239e259e06be015cd26d371be44056d632d7c0eaaaeb855fedbe0fde506
MD5 e2ab88344ae0d4dfcdaa43832b2f2bf3
BLAKE2b-256 df297d09f597215a5b9b61c3038f3720d74ab59dad81b0752ef1200d5d75f559

See more details on using hashes here.

File details

Details for the file ms_autoqc-1.0.1-py3-none-any.whl.

File metadata

  • Download URL: ms_autoqc-1.0.1-py3-none-any.whl
  • Upload date:
  • Size: 115.2 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.11.2

File hashes

Hashes for ms_autoqc-1.0.1-py3-none-any.whl
Algorithm Hash digest
SHA256 d1ff384793315e370c18468a30a0b3523f064bf235f990832f338745b0e4e713
MD5 b55b3a55bb2c6a92f8d9d8461f434161
BLAKE2b-256 32ea57bcbbdb5a5bcdc3b857cee145bfd4a900f8876f177548fc54dd7aa722dd

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page